Q: In your work with predictive analytics, what behavior or outcome do your models predict?

A: I work with health plans. The models primarily focus on predicting morbidity (i.e. frequency and severity) and cost outcomes (e.g. profitability). In limited cases, I have worked to predict specific events (e.g. readmission risk).

Q: How does predictive analytics deliver value at your organization – what is one specific way in which it actively drives decisions or operations?

A: Predictive analytics delivers value for our clients as they are better able to understand the financial consequences of various scenarios including maintaining current strategies or evaluating new ones.

Q: Can you describe a quantitative result, such as the predictive lift of your model or the ROI of an analytics initiative?

A: We constructed an algorithm that searches through millions of possibly interesting segmentations of a population to reveal the most important differentiators of a health plan’s profitability.

Q: What surprising discovery or insight have you unearthed in your data?

A: A surprising discovery was that post-risk adjustment, the members that may be costlier may also be driving up the profitability – which is counter-intuitive.

Q: Sneak preview: Please tell us a take-away that you will provide during your talk at Predictive Analytics World.

A: I hope that the audience finds value in the discussion of an approach to uncover drivers of profitability, and the specific drivers of profitability as measured over benefit year 2016 data for a number of health plans.